3 présentations

• 
  10h15 - 10h40

  Multi-Objective Optimization for Combinatorial Reverse Auctions in Electricity Consumption

  • Sifat E Jahan, prés., University of Regina
  • Malek Mouhoub, University of Regina

  Power outages are becoming more likely due to the growing electricity demand, prompting power companies to acquire electricity through e-actions. We explore several techniques to solve this NP-hard winner-determination problem that will procure energy from several suppliers by balancing multiple goals that can maximize resource acquisition and meet electricity demand. Nature-inspired methods offer a more efficient approach, balancing solution quality and computational time, unlike exact methods, which are inherently infeasible. The study examines Multi-Objective Optimization (MOO) techniques for solving Combinatorial Reverse Auction (CRA) problems, analyzing their effectiveness in solution quality and computational time. More precisely, we consider the Strength Pareto Evolutionary Algorithm (SPEA), the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the Pareto-Dominance Evolutionary Algorithm (EA).

• 
  10h40 - 11h05

  Enhancing the Resilience and Competitiveness of Canadian Wood Pellets through Bio-Hubs: A System Dynamics Approach

  • Omid Mohagheghi, prés., Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, QC, Canada
  • Fereshteh Mafakheri, École nationale d′administration publique (ENAP), Université du Québec, Montréal, Canada
  • Fuzhan Nasiri, Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, QC, Canada

  The global demand for wood pellets has surged in recent years, establishing them as a key commodity in the bioenergy sector. Canada, with its extensive forest resources, has significant potential to expand its role in the international wood pellet market. However, supply chain uncertainties and market volatility present challenges that could hinder industry growth. This study explores the impact of integrating bio-hubs into wood pellet supply chains (WPSCs) to enhance their adaptability and competitiveness. Utilizing a System Dynamics (SD) approach, the model evaluates how bio-hubs influence supply stability, demand responsiveness, and overall market positioning under diverse economic and supply conditions. Simulation outcomes indicate that bio-hubs can mitigate supply disruptions of up to 50% while supporting a substantial increase in demand from importing nations. By optimizing production and storage, bio-hubs contribute to stabilizing supply flows, ultimately strengthening Canada’s presence in the global wood pellet market. The findings emphasize the strategic importance of bio-hubs in fostering resilient bioenergy supply chains and provide valuable insights for industry stakeholders, policymakers, and researchers focusing on sustainable biomass utilization.
  Keywords: Bio-hubs, Wood pellet industry, Supply chain resilience, System Dynamics modeling, Bioenergy markets.

• 
  11h05 - 11h30

  Resilient and Sustainable Bioenergy Supply Chains: Insights on Storage and Replenishment Strategies under Risk Propagation

  • Mahsa Valipour, prés., Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada
  • Fereshteh Mafakheri, École nationale d’administration publique (ENAP), Université du Québec, Montréal, Canada
  • Chun Wang, Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada

  The impact of rising energy costs and climate pattern changes ripple through global economies, putting a spotlight on the importance of sustainable options. While biomass conversion into bioenergy presents a promising pathway, it is accompanied by inherent challenges that may hinder the full realization of its opportunities. Biomass replenishment depends on natural resources (e.g., forestry and agricultural residues), which can vary due to seasonal changes and geographic location. Moreover, transporting biomass presents logistical challenges and requires well-developed distribution networks, where factors such as long distances, infrastructure limitations, and weather conditions contribute to frequent transportation delays. Given the need to address these challenges and leverage opportunities offered by bioenergy production, this research aims to develop an agent-based decision-support framework integrated with advanced optimization algorithms. The proposed model focuses on key tactical and operational decisions related to storage and replenishment strategies within biomass supply chain networks. Given its computationally expensive function and substantial number of stochastic parameters integrated through probabilistic distributions, this problem is classified within the NP-hard category. To this end, we incorporate a simheuristic approach to derive the best possible solutions under specified conditions and constraints, while fulfilling the objective functions. The effectiveness of the proposed framework is demonstrated through a case study of remote off-grid communities in northern Quebec. This study provides valuable insights into electricity generation from biomass and an alternative fuel source, highlighting the resulting CO₂ emissions and cost implications of the proposed network.